Quiet Supersonic Flights 2018 (QSF18) Test: Galveston, Texas Risk Reduction for Future Community Testing with a Low-Boom Flight Demonstration Vehicle

The Quiet Supersonic Flights 2018 (QSF18) Program was designed to develop tools and methods for demonstration of overland supersonic flight with an acceptable sonic boom, and collect a large dataset of responses from a representative sample of the population. Phase 1 provided the basis for a low amplitude sonic boom testing in six different climate regions that will enable international regulatory agencies to draft a noise-based standard for certifying civilian supersonic overland flight. Phase 2 successfully executed a large scale test in Galveston, Texas, developed well documented data sets, calculated dose response relationships, yielded lessons, and identified future risk reduction activities

Scripted GUI Testing of Android Apps: A Study on Diffusion, Evolution and Fragility

Background. Evidence suggests that mobile applications are not thoroughly tested as their desktop counterparts. In particular GUI testing is generally limited. Like web-based applications, mobile apps suffer from GUI test fragility, i.e. GUI test classes failing due to minor modifications in the GUI, without the application functionalities being altered. Aims. The objective of our study is to examine the diffusion of GUI testing on Android, and the amount of changes required to keep test classes up to date, and in particular the changes due to GUI test fragility. We define metrics to characterize the modifications and evolution of test classes and test methods, and proxies to estimate fragility-induced changes. Method. To perform our experiments, we selected six widely used open-source tools for scripted GUI testing of mobile applications previously described in the literature. We have mined the repositories on GitHub that used those tools, and computed our set of metrics. Results. We found that none of the considered GUI testing frameworks achieved a major diffusion among the open-source Android projects available on GitHub. For projects with GUI tests, we found that test suites have to be modified often, specifically 5\%-10\% of developers' modified LOCs belong to tests, and that a relevant portion (60\% on average) of such modifications are induced by fragility. Conclusions. Fragility of GUI test classes constitute a relevant concern, possibly being an obstacle for developers to adopt automated scripted GUI tests. This first evaluation and measure of fragility of Android scripted GUI testing can constitute a benchmark for developers, and the basis for the definition of a taxonomy of fragility causes, and actionable guidelines to mitigate the issue.Comment: PROMISE'17 Conference, Best Paper Awar

Are Delayed Issues Harder to Resolve? Revisiting Cost-to-Fix of Defects throughout the Lifecycle

Many practitioners and academics believe in a delayed issue effect (DIE); i.e. the longer an issue lingers in the system, the more effort it requires to resolve. This belief is often used to justify major investments in new development processes that promise to retire more issues sooner. This paper tests for the delayed issue effect in 171 software projects conducted around the world in the period from 2006--2014. To the best of our knowledge, this is the largest study yet published on this effect. We found no evidence for the delayed issue effect; i.e. the effort to resolve issues in a later phase was not consistently or substantially greater than when issues were resolved soon after their introduction. This paper documents the above study and explores reasons for this mismatch between this common rule of thumb and empirical data. In summary, DIE is not some constant across all projects. Rather, DIE might be an historical relic that occurs intermittently only in certain kinds of projects. This is a significant result since it predicts that new development processes that promise to faster retire more issues will not have a guaranteed return on investment (depending on the context where applied), and that a long-held truth in software engineering should not be considered a global truism.Comment: 31 pages. Accepted with minor revisions to Journal of Empirical Software Engineering. Keywords: software economics, phase delay, cost to fi

A software testing estimation and process control model

The control of the testing process and estimation of the resource required to perform testing is key to delivering a software product of target quality on budget. This thesis explores the use of testing to remove errors, the part that metrics and models play in this process, and considers an original method for improving the quality of a software product. The thesis investigates the possibility of using software metrics to estimate the testing resource required to deliver a product of target quality into deployment and also determine during the testing phases the correct point in time to proceed to the next testing phase in the life-cycle. Along with the metrics Clear ratio. Chum, Error rate halving. Severity shift, and faults per week, a new metric 'Earliest Visibility' is defined and used to control the testing process. EV is constructed upon the link between the point at which an error is made within development and subsequently found during testing. To increase the effectiveness of testing and reduce costs, whilst maintaining quality the model operates by each test phase being targeted at the errors linked to that test phase and the ability for each test phase to build upon the previous phase. EV also provides a measure of testing effectiveness and fault introduction rate by development phase. The resource estimation model is based on a gradual refinement of an estimate, which is updated following each development phase as more reliable data is available. Used in conjunction with the process control model, which will ensure the correct testing phase is in operation, the estimation model will have accurate data for each testing phase as input. The proposed model and metrics have been developed and tested on a large-scale (4 million LOC) industrial telecommunications product written in C and C++ running within a Unix environment. It should be possible to extend this work to suit other environments and other development life-cycles

Effort estimation of FLOSS projects: A study of the Linux kernel

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 SpringerEmpirical research on Free/Libre/Open Source Software (FLOSS) has shown that developers tend to cluster around two main roles: “core” contributors differ from “peripheral” developers in terms of a larger number of responsibilities and a higher productivity pattern. A further, cross-cutting characterization of developers could be achieved by associating developers with “time slots”, and different patterns of activity and effort could be associated to such slots. Such analysis, if replicated, could be used not only to compare different FLOSS communities, and to evaluate their stability and maturity, but also to determine within projects, how the effort is distributed in a given period, and to estimate future needs with respect to key points in the software life-cycle (e.g., major releases). This study analyses the activity patterns within the Linux kernel project, at first focusing on the overall distribution of effort and activity within weeks and days; then, dividing each day into three 8-hour time slots, and focusing on effort and activity around major releases. Such analyses have the objective of evaluating effort, productivity and types of activity globally and around major releases. They enable a comparison of these releases and patterns of effort and activities with traditional software products and processes, and in turn, the identification of company-driven projects (i.e., working mainly during office hours) among FLOSS endeavors. The results of this research show that, overall, the effort within the Linux kernel community is constant (albeit at different levels) throughout the week, signalling the need of updated estimation models, different from those used in traditional 9am–5pm, Monday to Friday commercial companies. It also becomes evident that the activity before a release is vastly different from after a release, and that the changes show an increase in code complexity in specific time slots (notably in the late night hours), which will later require additional maintenance efforts